Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress in recent years and has become much more accessible to non-specialists with the development of ready-to-use tools. The study of oogenesis mechanisms and female reproductive success has also recently benefited from the development of efficient protocols for three-dimensional (3D) imaging of ovaries. Such datasets have a great potential for generating new quantitative data but are, however, complex to analyze due to the lack of efficient workflows for 3D image analysis.
View Article and Find Full Text PDFDeciphering mechanisms of oocyte development in the fish ovary still remain challenging, and a comprehensive overview of this process at the level of the organ is still needed. The recent development of optical tissue clearing methods has tremendously boosted the three-dimensional (3D) imaging of large size biological samples that are naturally opaque. However, no attempt of clearing on fish ovary that accumulates extremely high concentration of lipids within oocytes has been reported to date.
View Article and Find Full Text PDFThe phenotypic and functional dichotomy between IRF8 type 1 and IRF4 type 2 conventional dendritic cells (cDC1s and cDC2s, respectively) is well accepted; it is unknown how robust this dichotomy is under inflammatory conditions, when additionally monocyte-derived cells (MCs) become competent antigen-presenting cells (APCs). Using single-cell technologies in models of respiratory viral infection, we found that lung cDC2s acquired expression of the Fc receptor CD64 shared with MCs and of IRF8 shared with cDC1s. These inflammatory cDC2s (inf-cDC2s) were superior in inducing CD4 T helper (Th) cell polarization while simultaneously presenting antigen to CD8 T cells.
View Article and Find Full Text PDF